This actor implements a parameter estimator for Hidden Markov Models with Gaussian
Emissions. The base class ParameterEstimator performs the parameter estimation and
the HMMGaussianEstimator class contains density-specific methods for Gaussian emission
calculations and produces the relevant estimates at its output ports.

The output ports for a Gaussian HMM model are the mean and the standardDeviation
vectors of the possible hidden states in addition to the HMM parameters independent
from the emission density: transitionMatrix .
T
he mean is a double array output containing the mean estimates and
sigma is a double array output containing standard deviation estimates of
each mixture component. If the modelType is HMM, then an additional output,
transitionMatrix is provided, which is an estimate of the transition matrix
governing the Markovian process representing the hidden state evolution.
If the modelType is MM, this port outputs a double array with the prior
probability estimates of the mixture components.

The user-defined parameters are initial guesses for the model parameters, given by
m0, the mean vector guess, s0, the standard deviation vector guess,
prior, the prior state distribution guess, A0, the transition
matrix guess ( only for HMM). iterations is the number of EM iterations
allowed until convergence.
If, during iteration, the conditional log-likelihood of the observed
sequence given the parameter estimates converges to a value within likelihoodThreshold,
the parameter estimation stops iterating and delivers the parameter estimates.

clone

Clone this actor into the specified workspace. The new actor is
not added to the directory of that workspace (you must do this
yourself if you want it there).
The result is a new actor with the same ports as the original, but
no connections and no container. A container must be set before
much can be done with this actor.